Recent advancements in display technology are beginning to allow an extended range of chrominance, luminance and contrast values to be displayed. Technologies allowing for extensions in the range for luminance or brightness in image content are known as high dynamic range imaging, often shortened to HDR. HDR technologies focus on capturing, processing and displaying content of a wider dynamic range.
Although a number of HDR display devices have appeared, and cameras capable of capturing images with an increased dynamic range are being developed, there is still very limited HDR content available. While recent developments promise native capture of HDR content in the near future, they do not address existing content.
To prepare conventional, herein referred to as LDR for low dynamic range, content for HDR display devices, reverse or inverse tone mapping operators (ITMO) or color expansion operators can be employed. Such methods process notably the luminance information of colored areas in the image content with the aim of recovering or recreating the appearance of the original scene. Typically, ITMOs take a conventional (LDR) image as input, expand the luminance range of the colored areas of the image in a global manner, and subsequently process highlights or bright regions locally to enhance the HDR appearance of colors in the image.
Although several ITMO solutions exist, they focus at perceptually reproducing the appearance of the original scene and rely on strict assumptions about the content. Additionally, most expansion methods proposed in the literature are optimized towards extreme increases in dynamic range.
Typically, HDR imaging is defined by an extension in dynamic range between dark and bright values of luminance in colored areas combined with an increase in the number of quantization steps. To achieve more extreme increases in dynamic range, many methods combine a global expansion with local processing steps that enhance the appearance of highlights and other bright regions of images. Known global expansion steps proposed in the literature vary from inverse sigmoid, to linear or piecewise linear.
To enhance bright local features in an image, it is known to create a luminance expansion map, wherein each pixel of the image is associated with an expansion value to apply to the luminance of this pixel. In the simplest case, clipped regions in the image can be detected and then expanded using a steeper expansion curve, however such a solution does not offer sufficient control over the appearance of the image.